Assays

Simulation of OE mutants targetting enzymes in the model, combined with metabolite concentrations and enzyme fold change of from the 40 samples. For each second mutant the enzyme concentrations in case of OE and KO mutants in updated and the metabolite concentrations of the second sample are loaded in the model. Using this approach the model approximately predicts combinatorial effects of OE mutations with other mutations, perturbations and time series concentrations.

The associated zip files contains all input files and a Jupyter notebook to rerun sampled simmulations, combined simmulations, parameter scan for the model with addition of an oxygin inhibiton of LDH, local- and global-sensitivity analysis and plot simmulation output in various formats. In addition the zip file contains the py36.yaml file that can be used to recreate the model simmulation environment using Anaconda making all simmulations completely reproducable. All information on how to use ...

Training of the model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data.

Validation by simulating independent OE, KO mutant and perturbation samples, using sampling of the gausian distribution based on the mean and SD of measurements per sample. A 1000 samples of the gausian distribution of the mean and SD was performed per sample to show error in the measurements and how it propegates in predicted metabolite concentration in SS

Protein copy number at 6h, 12h, 24h, 48h, 72h, 96h, average values and SD for the measurements

Metabolomics time series measurements for internal metabolites for 6h, 24h and 48h for multiple experiments. Largely based on MAss spectrometry, bioluminescence kits to measure NAD, NADH at 24h, other time points are infered from relative measurements times the absolute measurements at 24h.

Measurements of external metabolites based on growth curve data. Flux estimates for uptake of external metabolites such as glucose and production rates for external metabolites lactate and acetate

Metabolic control analysis: Local control coefficients for 40 independent samples based on 100x sampling from the measurement distribution Global control analysis based on 100.000 Latin Hypercube sampling from the parameter search range (0.01-100 for Km values and 0.001-1000 for Vmax values)

Simple overview of all samples used for training, internal validation by copasi en external validation. Overview of samples metadata, mean metabolite concentration and enzyme concentrations used in the model. Only metabolites present in the model are shown.

Comparison of Kcat values from the model and values from literature.

Construction and manual curated Genome Scale Metabolitic model of M. hyopneumoniae. Dynamic flux balance analysis was performed for glucose uptake

Contains the analysis of the internal metabolite concentrations of the 40 independend samples Pearson correlation was used to generate heatmaps Pearson correlation with p-value cutof of 0.001 was used and as input for a correlation network (grouping using H-clust) Principal component analysis was performed on samples, F-ion and H-ion data combined and seperately Zip files contains the data (FC.txt), PCA and heatmap plots and the script to re-generate these plots